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  {
   "cell_type": "markdown",
   "id": "2b9582dc",
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   "source": [
    "# SingleStoreDB\n",
    "[SingleStoreDB](https://singlestore.com/) is a high-performance distributed SQL database that supports deployment both in the [cloud](https://www.singlestore.com/cloud/) and on-premises. It provides vector storage, and vector functions including [dot_product](https://docs.singlestore.com/managed-service/en/reference/sql-reference/vector-functions/dot_product.html) and [euclidean_distance](https://docs.singlestore.com/managed-service/en/reference/sql-reference/vector-functions/euclidean_distance.html), thereby supporting AI applications that require text similarity matching. This tutorial illustrates how to [work with vector data in SingleStoreDB](https://docs.singlestore.com/managed-service/en/developer-resources/functional-extensions/working-with-vector-data.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e4a61a4d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Establishing a connection to the database is facilitated through the singlestoredb Python connector.\n",
    "# Please ensure that this connector is installed in your working environment.\n",
    "!pip install singlestoredb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39a0132a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import getpass\n",
    "\n",
    "# We want to use OpenAIEmbeddings so we have to get the OpenAI API Key.\n",
    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6104fde8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
    "from langchain.text_splitter import CharacterTextSplitter\n",
    "from langchain.vectorstores import SingleStoreDB\n",
    "from langchain.document_loaders import TextLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b45113c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load text samples \n",
    "loader = TextLoader('../../../state_of_the_union.txt')\n",
    "documents = loader.load()\n",
    "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
    "docs = text_splitter.split_documents(documents)\n",
    "\n",
    "embeddings = OpenAIEmbeddings()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "535b2687",
   "metadata": {},
   "source": [
    "There are several ways to establish a [connection](https://singlestoredb-python.labs.singlestore.com/generated/singlestoredb.connect.html) to the database. You can either set up environment variables or pass named parameters to the `SingleStoreDB constructor`. Alternatively, you may provide these parameters to the `from_documents` and `from_texts` methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0b316bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup connection url as environment variable\n",
    "os.environ[\"SINGLESTOREDB_URL\"] = \"root:pass@localhost:3306/db\"\n",
    "\n",
    "# Load documents to the store\n",
    "docsearch = SingleStoreDB.from_documents(\n",
    "    docs,\n",
    "    embeddings,\n",
    "    table_name = \"notebook\", # use table with a custom name \n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0eaa4297",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = \"What did the president say about Ketanji Brown Jackson\"\n",
    "docs = docsearch.similarity_search(query)  # Find documents that correspond to the query\n",
    "print(docs[0].page_content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "86efff90",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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